Topic

Stated preference and monetary valuation

Stated preference methods ask people to choose between or value hypothetical options, revealing the trade-offs they would accept. Discrete choice experiments and best-worst scaling estimate how much each attribute matters, while contingent valuation asks directly about willingness to pay. Money values such as the value of statistical life allow health effects to enter cost-benefit analysis.

Concepts in this topic

• Anchoring BiasAnchoring bias is the pull of a starting value, such as an opening bid or the first offer in a time trade-off, on answers in health valuation surveys.
• Benefit TransferBenefit transfer reuses willingness-to-pay values from earlier studies, such as the value of a statistical life, to value health benefits in a new setting.
• Best-Worst ScalingBest-worst scaling (BWS) is a stated preference method in which people pick the best and worst item in each set, to rank priorities or value health states.
• Choice ExperimentA choice experiment is a stated-preference method in which respondents choose among systematically varied alternatives, allowing analysts to estimate the relative value of attributes from observed choice patterns under a specified random-utility model.
• Choice SetThe group of alternatives, typically hypothetical options and sometimes a status quo, presented to a respondent in a single choice task.
• Choice-Based ConjointChoice-based conjoint (CBC) is conjoint analysis in which patients or others choose between sets of described treatments or services rather than rate them.
• Conjoint AnalysisConjoint analysis is a family of stated preference methods estimating how people value treatment or service attributes from ratings, rankings or choices.
• Contingent ValuationContingent valuation is a stated-preference method that uses a structured hypothetical market to estimate how much people are willing to pay for a benefit or willing to accept as compensation for a loss.
• Contingent Valuation MethodThe contingent valuation method elicits a monetary value for a specified nonmarket health-related change by asking people what they would pay or accept in a carefully described hypothetical scenario.
• D-Efficient DesignA D-efficient design arranges feasible observations or choice tasks to provide high joint parameter precision, assessed by the determinant of a specified model’s expected information matrix.
• Discrete Choice ExperimentA discrete choice experiment, or DCE, presents respondents with repeated sets of hypothetical alternatives described by attributes and asks them to select a preferred option.
• Efficient DesignAn experimental design built to maximise the statistical information obtained from a given number of choice tasks.
• Experimental DesignThe systematic planning of an empirical study to allow valid causal inference, including decisions about randomisation, control groups, and study conditions.
• Latent Class ModelA statistical model that assumes a population consists of unobserved subgroups with distinct preferences, estimating both each subgroup's traits and individual membership probability.
• Marginal Rate of SubstitutionThe rate at which a consumer is willing to trade one good for another while keeping the same overall level of satisfaction.
• Meta-Regression TransferA form of benefit transfer in which a regression model estimated across many original studies predicts a value for a new context based on its characteristics.
• Monetary ValuationMonetary valuation expresses a health outcome or other non-market good in money terms, using stated preference, revealed preference or wellbeing methods.
• Orthogonal DesignAn experimental design for a choice experiment in which attribute levels are varied independently, so each attribute's effect on preference can be separated statistically.
• Part-Worth UtilityThe contribution of a single attribute level to an individual's overall utility for a good, estimated from a conjoint or choice experiment.
• Random Parameter ModelA discrete choice model that lets preference parameters vary randomly across individuals according to a specified distribution, rather than assuming identical preferences.
• Utility FunctionA mathematical representation of preferences that assigns a numerical value to each possible outcome, so higher-utility outcomes are preferred.
• Value of Statistical LifeA monetary estimate of the value society places on reducing the risk of death, derived from willingness to pay for a small risk reduction.
• Value of Statistical Life YearAn adaptation of the value of statistical life expressed per life-year rather than per life, adjusted for age and remaining life expectancy.
• Willingness to AcceptThe minimum compensation an individual would require to voluntarily give up a good or accept a worse outcome.
• Willingness to PayWillingness to pay (WTP) is the most money a person would give up for a health gain or other benefit, used to value outcomes in cost-benefit analysis.
• Willingness-to-Pay EstimationThe empirical process of measuring willingness to pay, typically through stated preference methods such as contingent valuation or discrete choice experiments.